code: def _randn_like(input: Tensor, mean: float, std: float) -> Tensor:
      x = torch.randn_like(
          input
      )  # Generating on GPU is fastest with `torch.randn_like(...)`
      if std != 1.0:  # `if` is cheaper than multiplication
          x *= std
      if mean != 0.0:  # `if` is cheaper than addition
          x += mean
      return x
  
file_path: kornia/kornia/augmentation/_2d/intensity/gaussian_noise.py
imports: from typing import Any, Dict, Optional, Tuple
  import torch
  from kornia.augmentation._2d.intensity.base import IntensityAugmentationBase2D
  from kornia.core import Tensor
label_desc: Use image node_id 1 for calling a global function with example usage: _randn_like(input, mean, std) and returns: x